Many retail stores could greatly benefit from the ability to match face recognition data to data obtained at a point-of-sale (PoS; i.e., checkout) location. While image analysis to identify faces can use one of many well-known techniques, identifying the face of a person at a PoS location and matching the appearance of the face with the corresponding transaction data remains a problem with a need for solution. The problem would be exacerbated if we do not assume a reasonably tight time synchronization between the video capture system and the PoS system. However, in reality, it is often the case where there could be random clock drifts between the two different systems, causing a mismatch between timestamp data in video capture devices and PoS systems. This creates the need for a time matching technique in order to synchronize data from both sources.